• 문화기술의 융합
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• 제6권4호
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• pp.219-224
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• 2020

Maecenas를 비롯한 다양한 초기 블록체인 기반 예술품 거래 플랫폼이 상업적으로 실패힌 주요한 원인 중 하나는 예술품을 지분화한 소유자가 소유권을 온전히 회복하기 위한 방법이 명확하지 않은 것이다. 본 논문에서는 블록체인 시스템 상에서 예술품을 지분화한 소유자가 지분을 회수하여 소유권을 온전히 회복하기 위한 절차를 제안했다. 제안한 절차를 활용하면 소유자와 투자자 사이에서 균형 가격을 찾은 후, 지분 공개 매수를 통해 소유권 회복이 가능하다. 균형 가격은 소유자가 비합리적으로 낮은 가격을 제안하는 것에 대해 불이익을 부여하고, 합리적인 가격을 결정하는 것에 대해 보상을 지급함으로써 유도될 수 있다. 제안한 소유권 회복 절차는 블록체인 기반 예술품 거래 플랫폼뿐만 아니라 다른 응용 분야의 블록체인 기반 거래 플랫폼에서도 활용될 수 있을 것으로 기대된다.

• 산업경영시스템학회지
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• 제41권4호
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• pp.179-188
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• 2018

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.